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جمع SkillsMP عدد ٢٦ من skills من CRAG666/dotfiles. افتح أي skill لمراجعة مصدره وتفاصيله.
عرض ٢٦ من أصل ٢٦ skills مجمعة.
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed…
لغة النص الأصلي: الإنجليزية
Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation…
لغة النص الأصلي: الإنجليزية
Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or…
لغة النص الأصلي: الإنجليزية
Convert heterogeneous documents and selected URIs to Markdown with Microsoft MarkItDown for text analysis, search, and LLM/RAG ingestion. Covers safe local conversion, streams, Office/PDF/data formats, batch workflows, plugins, vision OCR, Azure extraction,…
لغة النص الأصلي: الإنجليزية
Low-level plotting library for full customization. Use when you need fine-grained control over every plot element, creating novel plot types, or integrating with specific scientific workflows. Export to PNG/PDF/SVG for publication. For quick statistical plots…
لغة النص الأصلي: الإنجليزية
Create, analyze, and visualize complex networks and graphs in Python with NetworkX. Use when working with network/graph data structures, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks…
لغة النص الأصلي: الإنجليزية
Use NeuroKit2 to build or audit reproducible research workflows for physiological time-series preprocessing, event/interval analysis, multimodal alignment, variability, and complexity. Trigger when code imports neurokit2 or needs its current APIs, schemas,…
لغة النص الأصلي: الإنجليزية
GPU-accelerates scientific Python on NVIDIA hardware and verifies that the result is correct and faster. Use for CUDA/GPU optimization; CPU-bound NumPy, SciPy, pandas, scikit-learn, NetworkX, scikit-image, vector-search, image-processing, graph, simulation,…
لغة النص الأصلي: الإنجليزية
Search 11 academic literature APIs for papers, preprints, citations, and open-access full text, and return results with reproducible provenance. Covers PubMed, PMC (full text), Europe PMC (full-text and preprint search), bioRxiv, medRxiv, arXiv, OpenAlex,…
لغة النص الأصلي: الإنجليزية
Prior art patent search via Google Patents' JSON endpoint and Lens.org, with PDF download. Use when the user asks to search patents, prior art, "anterioridad", "patentes ancla", freedom-to-operate, novelty context, or patent landscaping. Covers query syntax,…
لغة النص الأصلي: الإنجليزية
High-performance genomic interval operations and bioinformatics file I/O on Polars DataFrames. Overlap, nearest, merge, coverage, complement, subtract for BED/VCF/BAM/GFF intervals. Streaming, cloud-native, faster bioframe alternative.
لغة النص الأصلي: الإنجليزية
High-performance DataFrame library for Python ETL, analytics, and pandas migration. Use for expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU…
لغة النص الأصلي: الإنجليزية
STRICT: stdlib idioms are mandatory — reinventing a stdlib feature is a defect, not a style choice. Apply whenever the user writes, refactors, optimizes, or reviews Python, including one-liners and code-review feedback. Verify non-trivial stdlib APIs against…
لغة النص الأصلي: الإنجليزية
Deep learning framework (PyTorch Lightning / lightning package). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard, MLflow), distributed training (DDP, FSDP,…
لغة النص الأصلي: الإنجليزية
Create and audit truthful, accessible, publication-ready scientific figures with Matplotlib, Seaborn, or Plotly. Use for figure design, multi-panel layouts, uncertainty and missing-data displays, color/contrast review, image metadata validation, and journal…
لغة النص الأصلي: الإنجليزية
Use whenever the user writes, drafts, revises, edits, polishes, or translates scientific or academic prose in ENGLISH - Q1 research articles, theses, dissertations, abstracts, introductions, methods, results, discussions, conclusions, acknowledgments,…
لغة النص الأصلي: الإنجليزية
Biological data toolkit. Sequence analysis, alignments, phylogenetic trees, diversity metrics (alpha/beta, UniFrac), ordination (PCoA), PERMANOVA, FASTA/Newick I/O, for microbiome analysis.
لغة النص الأصلي: الإنجليزية
Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML…
لغة النص الأصلي: الإنجليزية
Build, evaluate, and audit right-censored or competing-risk survival workflows with scikit-survival, including leakage-safe preprocessing, model selection, probability prediction, and censoring-aware metrics.
لغة النص الأصلي: الإنجليزية
Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin plots, pair plots, heatmaps. Built on matplotlib. For interactive…
لغة النص الأصلي: الإنجليزية
Explain and audit machine-learning predictions with SHAP. Use for selecting SHAP explainers and maskers, computing and validating feature attributions, handling multi-output explanations, and producing local or global SHAP visualizations.
لغة النص الأصلي: الإنجليزية
Guided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting. Use whenever a user wants to compare groups, test a hypothesis, analyze experimental or…
لغة النص الأصلي: الإنجليزية
Personal default directives for any generated or edited code: check for an existing library before writing anything, then emit the smallest correct code with no AI filler. Apply whenever writing, editing, refactoring, or emitting code in any language — new…
لغة النص الأصلي: الإنجليزية
STRICT structure-and-complexity layer for non-trivial code work: designing systems, writing new modules, refactoring, implementing algorithms, or making structural decisions. Complements code-style-defaults (form of the output) and python-native (Python…
لغة النص الأصلي: الإنجليزية
Enforces rigorous scientific methodology for machine learning experiments intended to support publication-grade claims (Q1 journals, conference papers, regulated decisions). Use this skill when designing an ML pipeline, splitting datasets, evaluating…
لغة النص الأصلي: الإنجليزية
Usar siempre que el usuario escriba, redacte, revise o traduzca texto científico/académico en ESPAÑOL: artículos, papers, tesis, abstracts, introducciones, metodologías, resultados, discusión, conclusiones, agradecimientos, revisiones de literatura, defensas,…
لغة النص الأصلي: الإسبانية